Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Rogers III, John G."'
Autor:
Aich, Shubhra, Wang, Wenshan, Maheshwari, Parv, Sivaprakasam, Matthew, Triest, Samuel, Ho, Cherie, Gregory, Jason M., Rogers III, John G., Scherer, Sebastian
High-speed off-road navigation requires long-range, high-resolution maps to enable robots to safely navigate over different surfaces while avoiding dangerous obstacles. However, due to limited computational power and sensing noise, most approaches to
Externí odkaz:
http://arxiv.org/abs/2403.11876
Autor:
Maheshwari, Parv, Wang, Wenshan, Triest, Samuel, Sivaprakasam, Matthew, Aich, Shubhra, Rogers III, John G., Gregory, Jason M., Scherer, Sebastian
Modeling the precise dynamics of off-road vehicles is a complex yet essential task due to the challenging terrain they encounter and the need for optimal performance and safety. Recently, there has been a focus on integrating nominal physics-based mo
Externí odkaz:
http://arxiv.org/abs/2311.00815
This paper presents a method for robust optimization for online incremental Simultaneous Localization and Mapping (SLAM). Due to the NP-Hardness of data association in the presence of perceptual aliasing, tractable (approximate) approaches to data as
Externí odkaz:
http://arxiv.org/abs/2209.14359
Autor:
Castro, Mateo Guaman, Triest, Samuel, Wang, Wenshan, Gregory, Jason M., Sanchez, Felix, Rogers III, John G., Scherer, Sebastian
Estimating terrain traversability in off-road environments requires reasoning about complex interaction dynamics between the robot and these terrains. However, it is challenging to create informative labels to learn a model in a supervised manner for
Externí odkaz:
http://arxiv.org/abs/2209.10788
When working alongside human collaborators in dynamic and unstructured environments, such as disaster recovery or military operation, fast field adaptation is necessary for an unmanned ground vehicle (UGV) to perform its duties or learn novel tasks.
Externí odkaz:
http://arxiv.org/abs/2205.03364
Traditional imitation learning provides a set of methods and algorithms to learn a reward function or policy from expert demonstrations. Learning from demonstration has been shown to be advantageous for navigation tasks as it allows for machine learn
Externí odkaz:
http://arxiv.org/abs/2108.00276
Autor:
Lukin, Stephanie M., Gervits, Felix, Hayes, Cory J., Leuski, Anton, Moolchandani, Pooja, Rogers III, John G., Amaro, Carlos Sanchez, Marge, Matthew, Voss, Clare R., Traum, David
ScoutBot is a dialogue interface to physical and simulated robots that supports collaborative exploration of environments. The demonstration will allow users to issue unconstrained spoken language commands to ScoutBot. ScoutBot will prompt for clarif
Externí odkaz:
http://arxiv.org/abs/1807.08074
Publikováno v:
Autonomous Robots; May2020, Vol. 44 Issue 5, p721-737, 17p
Autor:
Rogers III, John G., Trevor, Alexander J. B., Nieto-Granda, Carlos, Cunningham, Alex, Paluri, Manohar, Michael, Nathan, Dellaert, Frank, Christensen, Henrik I., Kumar, Vijay
Publikováno v:
Experimental Robotics (9783642285714); 2014, p433-446, 14p
Publikováno v:
Experimental Robotics (9783319000640); 2013, p231-243, 13p